Artificial intelligence (AI) and the metaverse are the two most important technology trends in e-learning in 2023.

Artificial intelligence is the ability of a machine to display the same capabilities as humans and is being used to improve and optimise various aspects of e-learning, such as:

  • Content adaptation: AI is able to analyse learner behaviour, learning preferences and level of knowledge to deliver targeted and personalised study materials.

 

  • Performance analysis and monitoring of learner progress: with this information AI can generate detailed reports on learner progress and identify areas for improvement.

 

  • Improve interaction and communication through virtual assistants.

 

The metaverse is a virtual world, one to which we will connect using a series of devices that will make us think that we are really inside it, interacting with all its elements.

 

In order to access the metaverse, we must do so through:

 

  • Virtual reality (VR): an environment of real-looking scenes and objects generated by computer technology, which creates the sensation of being immersed in it.

 

  • Augmented reality (AR): technology that allows virtual elements to be superimposed on our vision of reality.

 

  • Mixed Reality (MR): a mixture of the two previous ones, a mixture of physical and digital universes, which allows natural and intuitive 3D interactions between people, equipment and the environment.

 

As for the application of the metaverse in e-learning, students will be able to experience the concepts learned within real environments, enabling faster, more effective and lasting learning.

In terms of e-learning methodologies, the following are some of the ones that are trending in 2023:

 

  • TechQuilibrium: this is the point of balance between technology and the human factor within the company. Within e-learning, an intelligent use of digital tools is suggested, always starting from a human vision.

 

  • Mobile Learning: is a way of accessing learning content through mobile devices, making it unnecessary to have access to a computer, information and results.

 

  • Learning Loops: this consists of improving learning processes based on the information and results we gather from previous circles. This makes the second learning loop better than the first, so it is repeated to evolve.

 

  • Learning Analytics: is the measurement, collection, analysis and reporting of data about learners and their environments in order to understand and optimise learning and the environment in which it occurs.